> -----Original Message-----
> From: r-help-bounces@stat.math.ethz.ch
> [mailto:r-help-bounces@stat.math.ethz.ch] On Behalf Of Doran, Harold
> Sent: Tuesday, June 06, 2006 5:08 PM
> To: r-help@stat.math.ethz.ch
> Subject: [R] Subset data in long format
>
> I have data in a "long" format where each row is a student
> and each student occupies multiple rows with multiple
> observations. I need to subset these data based on a
> condition which I am having difficulty defining.
>
> The dataset I am working with is large, but here is a simple
> data structure to illustrate the issue
>
> tmp <- data.frame(id = 1:3, matrix(rnorm(30), ncol=10) ) long
> <- reshape(tmp, idvar='id', varying=list(names(tmp)[2:11]),
> v.names=('item'),timevar='position' , direction='long') long
> <- long[order(long$id) , ] long <- long[c(-2,-13),]
>
> What I need to do is subset these data so I have the first 6
> rows for each unique ID. The problem is that the data are
> unbalanced in that each ID has a different number of
> observations (which I why I removed obs 2 and 13).
>
> If the data were balanced, the subset would be trivial and I
> could just do
>
> long <- subset(long, position < 7)
>
> However, the data are not balanced. Consequently, if I were
> to do this for the unbalanced data I would not have the first
> 6 obs for the first ID. I would only have the first 5.
> Theoretically, what I want for id1(and for each unique id) is this
>
> ID1 <- subset(long, id==1)
> ID1[1:6,]
>
> However, the goal is to subset the entire dataframe at once
> such that the subset returns a new dataframe with the first 6
> rows for each unique id. Is there a feasible method for doing
> this subset that anyone can suggest? My actual dataset has
> more than 24,000 unique ids, so I am hoping to avoid looping
> through this if possible.
>
> Thanks,
> Harold
>
>
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>
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